(R1) Robotics Systems Fundamentals

Course Title: Robotics Systems Fundamentals

Duration: 8 Hours

Course Modalities:

• In-Classroom (166 West Main Street, Suite 204B, Mesa, AZ 85201)

Robots are entering warehouses, hospitals, construction sites, and corporate facilities at an accelerating pace, but most professionals who work with or around these systems have no structured understanding of how they actually function. This course provides that foundation. It introduces Robotics Builders to the complete anatomy of a robotic system: how robots are structured, how they execute movement, how they perceive their environment through sensors, how they make decisions through control loops, why they fail in real-world conditions, and how all of these layers integrate into a functioning whole.

Participants will develop a systems-level mental model of robotics that applies across platforms, industries, and robot types, from humanoid robots to industrial arms to mobile delivery systems. This course establishes the technical literacy required for all subsequent courses in the Robotics Systems Certification and for any professional role that involves designing, deploying, operating, or managing robotic systems.

See inside a real humanoid robot. In this course, the ASIMOV V1 is taken apart layer by layer: 25 actuators, integrated camera, IMU, edge compute, and cloud connectivity. You will trace every subsystem, every data flow, and every failure point on a production-grade humanoid platform, not a textbook diagram. During live demonstrations, you will observe each subsystem in action and interact with the robot's digital twin to explore how architectural decisions affect real system behavior."

This full-day, hands-on course focuses on understanding how robotic systems are architected, how movement is commanded and executed, how sensors collect and interpret environmental data, how control loops translate input into action, and why robotic systems fail under real-world conditions. Participants will explore each layer of a robotic system progressively, building a complete mental model from architecture through integration.

The course emphasizes transferable systems thinking rather than platform-specific tooling, enabling learners to apply their understanding across any robotic system they encounter, whether it is a humanoid robot, an industrial manipulator, or an autonomous mobile platform. Topics include system architecture, actuator types and motor control, sensor modalities and signal interpretation, closed-loop control design, common failure modes and their root causes, and end-to-end system integration.

By the end of the course, learners will understand how a complete robotic system operates from sensors through decision-making to physical action, and why systems break down when these layers are poorly designed or integrated, setting the stage for robot operation, perception, behavior design, and autonomous systems in subsequent courses.

Students will be able to:

• Describe the architecture of a robotic system and identify the role of each major subsystem including compute, actuation, sensing, and control
• Explain how robots execute movement through actuators, motors, and command interfaces, and distinguish between different actuator types and their applications
• Describe how robots perceive their environment through camera systems, inertial measurement units, and other sensor modalities, and interpret the data these sensors produce
• Explain how control loops connect sensor input to physical action and why closed-loop control is essential for reliable robot behavior
• Identify common failure modes in real-world robotic systems including sensor noise, latency, mechanical drift, and environmental mismatch, and explain their root causes
• Trace the flow of information through a complete robotic system from environmental input through processing, decision-making, and physical output
• Evaluate how architectural decisions at each layer affect overall system reliability, performance, and suitability for a given deployment environment

Modules:

• Robotic Systems Architecture: Subsystems and Data Flow
• Architecture Patterns: Centralized, Distributed, and Deployment Decisions
• How Robots Move: Actuator Types and Motion
• Command Execution: From Software Intent to Physical Action
• How Robots Sense: Sensor Types and Raw Data
• Signal Interpretation and Reliability
• The Control Loop: From Input to Action
• Failure Modes in Real-World Robotics
• End-to-End Robotic System Integration
• Final Exam

AI Gurus Academy is Arizona’s leading AI and robotics training provider, delivering motion capture–enabled and hands-on education across Phoenix, Mesa, Scottsdale, Tempe, Chandler, Gilbert, Glendale, Peoria, Surprise, and the greater Phoenix metropolitan area, with online training available worldwide. Our programs now integrate advanced robotics systems training using the Asimov humanoid platform from Menlo Research, giving learners direct exposure to real-world robotic operation, perception, behavior design, and autonomous systems.

AI Gurus Academy provides applied artificial intelligence training, robotics education, and motion capture–enabled learning for individuals, creators, and organizations. We serve students, professionals, and employers across Arizona while supporting global learners through virtual instruction. We are the premier choice for individuals and organizations seeking to upskill in AI, robotics, and intelligent system deployment.

Our expanded programs cover AI fundamentals, applied AI workflows, generative AI, automation, computer vision, robotics systems, robot operation and control, perception systems, behavior design, and autonomous robotics. Training combines real-world instruction with hands-on interaction using the Asimov humanoid robot, enabling learners to understand how AI integrates with physical systems in production environments.

Our motion capture studio supports AI and robotics training across the Phoenix metro, including Mesa, Phoenix, Tempe, Scottsdale, and Chandler, enabling advanced learning in: AI-driven animation and simulation; computer vision and human movement modeling; robotics perception and sensor integration; AI for gaming, XR, robotics, and digital humans; and motion data for machine learning, autonomy development, and synthetic data generation.